Potentials of artificial intelligence in construction management

Eber, Wolfgang

doi:10.2478/otmcj-2020-0002

Cited by 22 publications

(17 citation statements)

References 25 publications

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“…The study represents industrial connectivity as a potential aspect as it ensures the benefits associated with Industry 4.0 technologies. Also, Eber ( 2020 ) analyzed the scope of AI concerning construction management. The study focuses on the various aspects of in situ coordination.…”

Section: Literature Reviewmentioning

confidence: 99%

Identifying issues in adoption of AI practices in construction supply chains: towards managing sustainability

Singh

Dwivedi

Agrawal³

et al. 2023

Oper Manag Res

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The fragmented nature of construction industry coupled with its complex and dynamic nature demands for innovative technologies to record better performance in project execution. In this respect, Artificial Intelligence (AI) based techniques posit a viable means to attain requisite efficiency in performance and alleviate the productivity of construction organizations. The adoption of sustainable practices in Construction Supply Chains (CSCs) lowers the environmental impact, lowers the risk of failure, and boosts competitiveness. The present study attempts to unearth potential issues in the adoption of AI practices in CSCs. Initially, the study identifies potential issues in the implementation of AI-based frameworks in CSCs by performing an extensive literature review and brainstorming sessions with industry experts. The exercise results in identifying 17 critical issues confronting the adoption of AI in CSCs which were subsequently subjected to fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) approach. The findings from the study reveal that “Lack of trust in AI outcomes”, “Exploitation by hackers, cybercrimes and privacy intrusion”, “Risk and cost associated with construction projects”, “Uncertain processing and functions of AI algorithms”, and “Unclear profits and advantages” were the top five influential causal issues that affect the adoption of AI in CSCs. This study is a novel attempt in the direction to identify and prioritize the potential issues in the adoption of AI-based frameworks in the Indian CSCs.

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Section: Literature Reviewmentioning

confidence: 99%

Identifying issues in adoption of AI practices in construction supply chains: towards managing sustainability

Singh

Dwivedi

Agrawal³

et al. 2023

Oper Manag Res

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“…The amount of resource waste is growing rapidly on a yearly basis due to rapid development [48]. Companies are becoming more waste aware and are implementing proactive data-driven approaches that minimize waste through analytics [49]. Waste analytics is dependent on different sources of data, such as building design, material properties, and construction strategies.…”

Section: Waste Management and Resourcesmentioning

confidence: 99%

“…In addition, machine learning can analyze complex tasks and establish variables that may adversely affect a project. According to Eber [49], artificial neural networks are applied to analyze start dates, employee performance, material costs, etc. However, the platform's efficiency depends on the accuracy of previous projects and may not be feasible for smaller construction companies [22].…”

Section: Prominent Artificial Intelligence Technologies In Constructi...mentioning

confidence: 99%

“…The analysis improves efficiency, accuracy, and quality by extracting information via reliable automated systems [50]. INSITE's technology is currently under development to combine computer vision, deep learning, and aerospace algorithms [58], making the machines smarter by estimating the machine position and visual perceptions [49]. These technologies will ensure construction processes are reliable, productive, and efficient.…”

Section: Construction Phasementioning

confidence: 99%

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Opportunities and Adoption Challenges of AI in the Construction Industry: A PRISMA Review

Regona

Yiğitcanlar

Xia

et al. 2022

Journal of Open Innovation: Technology, Market, and Complexity

211

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Artificial intelligence (AI) is a powerful technology with a range of capabilities, which are beginning to become apparent in all industries nowadays. The increased popularity of AI in the construction industry, however, is rather limited in comparison to other industry sectors. Moreover, despite AI being a hot topic in built environment research, there are limited review studies that investigate the reasons for the low-level AI adoption in the construction industry. This study aims to reduce this gap by identifying the adoption challenges of AI, along with the opportunities offered, for the construction industry. To achieve the aim, the study adopts a systematic literature review approach using the PRISMA protocol. In addition, the systematic review of the literature focuses on the planning, design, and construction stages of the construction project lifecycle. The results of the review reveal that (a) AI is particularly beneficial in the planning stage as the success of construction projects depends on accurate events, risks, and cost forecasting; (b) the major opportunity in adopting AI is to reduce the time spent on repetitive tasks by using big data analytics and improving the work processes; and (c) the biggest challenge to incorporate AI on a construction site is the fragmented nature of the industry, which has resulted in issues of data acquisition and retention. The findings of the study inform a range of parties that operate in the construction industry concerning the opportunities and challenges of AI adaptability and help increase the market acceptance of AI practices.

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“…The very engineering-like approach to optimize this with respect to the consumption of resources focuses on the total set of processes, in particular avoiding any idle running as the major wastage [21,22,23]. In order to do so under the pressure of tight schedules and low margins, pains are taken to couple processes as closely as possible, thus minimizing time floats and tolerance regarding perfection of pre-products [24].…”

Section: Introductionmentioning

confidence: 99%

Explicit Evaluation of Complexity in Construction and Real Estate Management

Eber¹

2020

Proceedings of the Creative Construction E-Conference 2020

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Complexity has become a major keyword when it comes to organization issues in Construction and Real Estate Management. Expressed via many different theoretical definitions, complexity in terms of management represents the part of organization which is simply not manageable. Therefore, reduction of complexity by separating a system into independent well-defined and well-controlled subsystems becomes a major task. However, since construction and real estate projects are becoming larger, encompassing higher volumes as well as higher numbers of participants and are nonetheless subjected to strongly limited time-frames and budgets on tight markets, efficient organization developed into the crucial issue to stand a competition successfully. On this background, engineering naturally focuses on saving costly resources, where the explicit value of a single measure can easily be derived from the cost of the resource and the duration of the therewith reduced time floats. This leads to well-known concepts, e.g. just-in-time-delivery, where a system is optimized with respect to physical resources as well as virtual resources like storage space or reserve time. However, as this strategy clearly saves explicit local resources, concurrently the coupling of processes via the required availability of physical and virtual resources, ranging from pre-products to decisions, plans and responsibilities, is strongly increased and, thus, complexity is reintroduced to a significant degree. This paper proposes an approach on the basis of Systems Theory providing an explicit measure to evaluate the increase of complexity in relation to possibly saved resources. Since cost of complexity are not given a priori but result from possible deviations, this article investigates the propagation of virtual uncertainties of real and abstract pre-products through a network of given complexity. On this basis, some general rules are derived allowing to maintain the balance between saving resources and the therewith increasing cost of the consequently rising complexity.

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Potentials of artificial intelligence in construction management

Cited by 22 publications

References 25 publications

Identifying issues in adoption of AI practices in construction supply chains: towards managing sustainability

Identifying issues in adoption of AI practices in construction supply chains: towards managing sustainability

Opportunities and Adoption Challenges of AI in the Construction Industry: A PRISMA Review

Explicit Evaluation of Complexity in Construction and Real Estate Management

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